Download or read book The Evidential Foundations of Probabilistic Reasoning written by David A. Schum and published by Northwestern University Press. This book was released on 2001 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this work Schum develops a general theory of evidence as it is understood and applied across a broad range of disciplines and practical undertakings. He include insights from law, philosophy, logic, probability, semiotics, artificial intelligence, psychology and history.
Download or read book Probabilistic Reasoning in Intelligent Systems written by Judea Pearl and published by Elsevier. This book was released on 2014-06-28 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
Download or read book Handbook of Legal Reasoning and Argumentation written by Giorgio Bongiovanni and published by Springer. This book was released on 2018-07-02 with total page 764 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook addresses legal reasoning and argumentation from a logical, philosophical and legal perspective. The main forms of legal reasoning and argumentation are covered in an exhaustive and critical fashion, and are analysed in connection with more general types (and problems) of reasoning. Accordingly, the subject matter of the handbook divides in three parts. The first one introduces and discusses the basic concepts of practical reasoning. The second one discusses the general structures and procedures of reasoning and argumentation that are relevant to legal discourse. The third one looks at their instantiations and developments of these aspects of argumentation as they are put to work in the law, in different areas and applications of legal reasoning.
Download or read book Rethinking Evidence written by William Twining and published by Cambridge University Press. This book was released on 2006-06-01 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Law of Evidence has traditionally been perceived as a dry, highly technical, and mysterious subject. This book argues that problems of evidence in law are closely related to the handling of evidence in other kinds of practical decision-making and other academic disciplines, that it is closely related to common sense and that it is an interesting, lively and accessible subject. These essays develop a readable, coherent historical and theoretical perspective about problems of proof, evidence, and inferential reasoning in law. Although each essay is self-standing, they are woven together to present a sustained argument for a broad inter-disciplinary approach to evidence in litigation, in which the rules of evidence play a subordinate, though significant, role. This revised and enlarged edition includes a revised introduction, the best-known essays in the first edition, and chapters on narrative and argumentation, teaching evidence, and evidence as a multi-disciplinary subject.
Download or read book A Probabilistic Analysis of the Sacco and Vanzetti Evidence written by Joseph B. Kadane and published by John Wiley & Sons. This book was released on 2011-09-26 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Probabilistic Analysis of the Sacco and Vanzetti Evidence is aBayesian analysis of the trial and post-trial evidence in the Saccoand Vanzetti case, based on subjectively determined probabilitiesand assumed relationships among evidential events. It applies theideas of charting evidence and probabilistic assessment to thiscase, which is perhaps the ranking cause celebre in all of Americanlegal history. Modern computation methods applied to inferencenetworks are used to show how the inferential force of evidence ina complicated case can be graded. The authors employ probabilisticassessment to obtain opinions about how influential each group ofevidential items is in reaching a conclusion about the defendants'innocence or guilt. A Probabilistic Analysis of the Sacco and Vanzetti Evidence holdsparticular interest for statisticians and probabilists in academiaand legal consulting, as well as for the legal community,historians, and behavioral scientists. It combines structural andprobabilistic ideas in the analysis of masses of evidence fromevery recognized logical species of evidence. Twenty-eight chartsshow the chains of reasoning in defense of the relevance ofevidentiary matters and a listing of trial witnesses who providedthe evidence. References include nearly 300 items drawn from thefields of probability theory, history, law, artificialintelligence, psychology, literature, and other areas.
Download or read book Foundations of Probabilistic Programming written by Gilles Barthe and published by Cambridge University Press. This book was released on 2020-12-03 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of the theoretical underpinnings of modern probabilistic programming and presents applications in e.g., machine learning, security, and approximate computing. Comprehensive survey chapters make the material accessible to graduate students and non-experts. This title is also available as Open Access on Cambridge Core.
Download or read book Logical Foundations of Probability written by Rudolf Carnap and published by . This book was released on 1962 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Classic Works of the Dempster Shafer Theory of Belief Functions written by Ronald R. Yager and published by Springer. This book was released on 2008-01-22 with total page 813 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a collection of classic research papers on the Dempster-Shafer theory of belief functions. The book is the authoritative reference in the field of evidential reasoning and an important archival reference in a wide range of areas including uncertainty reasoning in artificial intelligence and decision making in economics, engineering, and management. The book includes a foreword reflecting the development of the theory in the last forty years.
Download or read book Systematic Introduction to Expert Systems written by Frank Puppe and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: At present one of the main obstacles to a broader application of expert systems is the lack of a theory to tell us which problem-solving methods areavailable for a given problem class. Such a theory could lead to significant progress in the following central aims of the expert system technique: - Evaluating the technical feasibility of expert system projects: This depends on whether there is a suitable problem-solving method, and if possible a corresponding tool, for the given problem class. - Simplifying knowledge acquisition and maintenance: The problem-solving methods provide direct assistance as interpretation models in knowledge acquisition. Also, they make possible the development of problem-specific expert system tools with graphical knowledge acquisition components, which can be used even by experts without programming experience. - Making use of expert systems as a knowledge medium: The structured knowledge in expert systems can be used not only for problem solving but also for knowledge communication and tutorial purposes. With such a theory in mind, this book provides a systematic introduction to expert systems. It describes the basic knowledge representations and the present situation with regard tothe identification, realization, and integration of problem-solving methods for the main problem classes of expert systems: classification (diagnostics), construction, and simulation.
Download or read book Artificial Intelligence written by David L. Poole and published by Cambridge University Press. This book was released on 2017-09-25 with total page 821 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence presents a practical guide to AI, including agents, machine learning and problem-solving simple and complex domains.
Download or read book A Mathematical Theory of Evidence written by Glenn Shafer and published by Princeton University Press. This book was released on 2020-06-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Both in science and in practical affairs we reason by combining facts only inconclusively supported by evidence. Building on an abstract understanding of this process of combination, this book constructs a new theory of epistemic probability. The theory draws on the work of A. P. Dempster but diverges from Depster's viewpoint by identifying his "lower probabilities" as epistemic probabilities and taking his rule for combining "upper and lower probabilities" as fundamental. The book opens with a critique of the well-known Bayesian theory of epistemic probability. It then proceeds to develop an alternative to the additive set functions and the rule of conditioning of the Bayesian theory: set functions that need only be what Choquet called "monotone of order of infinity." and Dempster's rule for combining such set functions. This rule, together with the idea of "weights of evidence," leads to both an extensive new theory and a better understanding of the Bayesian theory. The book concludes with a brief treatment of statistical inference and a discussion of the limitations of epistemic probability. Appendices contain mathematical proofs, which are relatively elementary and seldom depend on mathematics more advanced that the binomial theorem.
Download or read book Probabilistic Reasoning in Expert Systems written by Richard E. Neapolitan and published by CreateSpace. This book was released on 2012-06-01 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is a reprint of the seminal 1989 book Probabilistic Reasoning in Expert systems: Theory and Algorithms, which helped serve to create the field we now call Bayesian networks. It introduces the properties of Bayesian networks (called causal networks in the text), discusses algorithms for doing inference in Bayesian networks, covers abductive inference, and provides an introduction to decision analysis. Furthermore, it compares rule-base experts systems to ones based on Bayesian networks, and it introduces the frequentist and Bayesian approaches to probability. Finally, it provides a critique of the maximum entropy formalism. Probabilistic Reasoning in Expert Systems was written from the perspective of a mathematician with the emphasis being on the development of theorems and algorithms. Every effort was made to make the material accessible. There are ample examples throughout the text. This text is important reading for anyone interested in both the fundamentals of Bayesian networks and in the history of how they came to be. It also provides an insightful comparison of the two most prominent approaches to probability.
Download or read book Cognition and Chance written by Raymond S. Nickerson and published by Psychology Press. This book was released on 2004-06-24 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an overview of the necessary information needed to make educational assumptions about the statistical or probable characteristics of a situation. The book can be used as a supplemental text in courses on probability, logic, statistics,
Download or read book Probabilistic Logics and Probabilistic Networks written by Rolf Haenni and published by Springer Science & Business Media. This book was released on 2010-11-19 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: While probabilistic logics in principle might be applied to solve a range of problems, in practice they are rarely applied - perhaps because they seem disparate, complicated, and computationally intractable. This programmatic book argues that several approaches to probabilistic logic fit into a simple unifying framework in which logically complex evidence is used to associate probability intervals or probabilities with sentences. Specifically, Part I shows that there is a natural way to present a question posed in probabilistic logic, and that various inferential procedures provide semantics for that question, while Part II shows that there is the potential to develop computationally feasible methods to mesh with this framework. The book is intended for researchers in philosophy, logic, computer science and statistics. A familiarity with mathematical concepts and notation is presumed, but no advanced knowledge of logic or probability theory is required.
Download or read book Evidence Matters written by Susan Haack and published by Cambridge University Press. This book was released on 2014-07-28 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: Is truth in the law just plain truth - or something sui generis? Is a trial a search for truth? Do adversarial procedures and exclusionary rules of evidence enable, or impede, the accurate determination of factual issues? Can degrees of proof be identified with mathematical probabilities? What role can statistical evidence properly play? How can courts best handle the scientific testimony on which cases sometimes turn? How are they to distinguish reliable scientific testimony from unreliable hokum? These interdisciplinary essays explore such questions about science, proof, and truth in the law. With her characteristic clarity and verve, Haack brings her original and distinctive work in theory of knowledge and philosophy of science to bear on real-life legal issues. She includes detailed analyses of a wide variety of cases and lucid summaries of relevant scientific work, of the many roles of the scientific peer-review system, and of relevant legal developments.
Download or read book Probabilistic Reasoning in Expert Systems written by Richard E. Neapolitan and published by Wiley-Interscience. This book was released on 1990-03-16 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Addresses the use probability theory as a tool for designing with and implementing uncertainity reasoning. Provides many concrete algorithms, explores techniques for solving multimembership classification problems not based directly on causal networks, and offers practical recommendations, matching specific methods with sample expert systems.
Download or read book Statistical Inference as Severe Testing written by Deborah G. Mayo and published by Cambridge University Press. This book was released on 2018-09-20 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.
